CRITICAL SUCCESS FACTORS OF STRATEGIC ACCOUNTING INFORMATION SYSTEM AND IT’S RELATION WITH STRATEGIC DECISIONS EFFECTIVENESS

This paper attempts to explain the critical success factors of strategic information system (SIS) and it’s relation with strategic decisions effectiveness. An analysis demonstrated that SIS advancement began from a mechanical concentration toward a procedure concentrating on complementary association with firms’ system and notwithstanding setting business technique and driving hierarchical change and structure. Primarily, the best SIS is coordinated such that better fits the affiliation properties for the culture, structure, style and limits. Finally, strategist’s effort to improve the fragmented data they have dependent on their past experience and claim intellectual styles. In this way any choices made would be made reliant on the strategist’s qualities, convictions and experience, which at last could confine the decisions that they make. Basically, then qualities fill in as outlines or establishments for deciding, tackling issues and settling clashes.

Dynamical Outcome Modeling of Fragmented Intensive Longitudinal Data

The advent of new sensing technologies has enabled the collection of high frequency individual data. Not only can this allow for the identification of personalized behavior models, it also opens up the possibility of developing just-in-time interventions that leverage the information collected to determine when and which micro intervention should be provided. However, there are significant challenges in the analysis of this type of data. First, due to the high rate of data collection, one can no longer assume that the stimulus (independent excitation or micro intervention) only has an instantaneous effect on the outcome, one has to also allow for delayed effects. Moreover, one is also frequently faced with fragmented data; i.e., poor placement of sensors, non-wear of the data collecting device and/or external disturbances can lead to intervals of time where the data collected is not reliable; i.e., missing or corrupted. To deal with these challenges, we leverage concepts from the areas of dynamical systems and signal processing to develop tools that i) can identify models that take into account the delayed stimuli effects and ii) are able to handle fragmented data. In this paper, we provide both the mathematical foundation of the tools proposed and the description of a package that implements them. We also discuss ways to interpret the results obtained.

Design of Open Knowledge Platform Based On Knowledge Base Utilization Model And Service Scenario To Support Solutions Of Regional Issues

Open knowledge platform can provide a purified knowledge base. Thus, we build a platform for several application areas in a cloud computing that supports APIs for various data based on a knowledge utilization model. The goal of this platform is to maximize the utilization of the knowledge base. In order to achieve this goal, we designed the structure of this platform as an open knowledge platform. The targets of the design are to maximize the utilization of data linkage, to expand it to national common knowledge and to increase its usability by providing services with knowledge graphs. In order to design the platform we identified users, information sources, and infrastructures. In the process, we found it is crucial to specify roles and services to the users of the platform. The requirements are induced from a utilization model and scenario of the service based on the knowledge graph. With the service scenario, stakeholders of the platform started narrow down function modules needed to support the service. One of the modules is a national common knowledge in the knowledge base, which provide essential connected knowledge to support solving regional problems of government such as earthquake, flooding. To increase the usability of data scattered by departments and agencies, data linkage, and knowledge between fragmented data sets is included in this platform. Subsequently, we designed modules to support the effective utilization of this knowledge information. Also, we found that a cloud infrastructure instead of in-house hardware and software could provide flexible and compatible services for the platform. Moreover, the cloud system has advantages on big data analysis and distributed system interconnection. Utilization model and scenario-based process modeling provide a systematic approach to design an open knowledge platform that supports many required components enabling interoperability, compatibility, and connectivity among other knowledge bases..

Artful-Geoscience: Co-Creating Urban Subsurface Futures? A discussion and an invitation.

<p>The urban subsurface is key to developing sustainable urban futures (SDG 11). Yet, as is well acknowledged, geoscientists face many challenges in engaging stakeholders and communities with the urban subsurface, as well as the challenges associated wtih fragmented data sources, knowledge gaps, citizen ‘oversight,’ and challenging subsurface cultural associations (Bricker et al. 2017, 2019). In this paper we present a case for the value of the intersections between geoscience and creative practices (from visual methods to participatory arts) in helping to address some of these challenges. To make our case we present preliminary findings from a collaboration between geoscientists and science communicators based at the British Geological Survey, and a cultural geographer experienced in researching and creating art-science collaborations. We explore three things:</p><p>We close our discussion with an invitation to join us in forming a network exploring the potential of art-geoscience collaborations for understanding, using and preserving the urban subsurface. </p>

DATA TRANSFER RATE IN NOISY CHANNELS OF WIRELESS NETWORKS

Analysis of new technologies IEEE 802.11ac/ax of wireless networks showed that increasing their noise immunity is an actual task. The article studies the efficiency of fragmented data frames transmission. Comparison of the efficiencies in the case of retransmission of the corrupted original frame and in the case of its fragmentation in a wide range of the physical data transfer rates is carried out.

Relevance of the Isoflavone Absorption and Testicular Function: A Systematic Review of Preclinical Evidence

Isoflavone is a phytoestrogen found in different types of food that can act as endocrine disrupters leading to testicular dysfunction. Currently, fragmented data on the action of this compound in the testicles make it difficult to assess its effects to define a safe dose. Thus, we systematically reviewed the preclinical evidence of the impact of isoflavone on testicular function. We also determined which form (aglycones or glycosylated) was the most used, which allowed us to understand the main biological processes involved in testicular function after isoflavone exposure. This systematic review was carried out according to the PRISMA guidelines using a structured search on the biomedical databases MEDLINE (PubMed), Scopus, and Web of Science, recovering and analyzing 22 original studies. The bias analysis and the quality of the studies were assessed by the criteria described in the risk of bias tool developed by SYRCLE (Systematic Review Centre for Laboratory Animal Experimentation). The aglycones and glycosylated isoflavones proved to be harmful to the reproductive health, and the glycosylates at doses of 50, 100, 146, 200, 300, 500, and 600 mg/kg, in addition to 190 and 1000 mg/L, appear to be even more harmful. The main testicular pathologies resulting from the use of isoflavones are associated with Leydig cells resulting from changes in molecular functions and cellular components. The most used isoflavone to evaluate testicular changes was the genistein/daidzein conjugate. The consumption of high doses of isoflavones promotes changes in the functioning of Leydig cells, inducing testicular changes and leading to infertility in murine models.

Pulmonary tuberculosis co-infection and COVID-19 in Senegal

New Coronavirus Disease (SARS-CoV-2) is responsible for the severe acute respiratory syndrome. Appeared in Wuhan, China, in December 2019, it affects more than 188 countries around the world to date. Africa is not spared by this pandemic (COVID-19), which is on the rise. Tuberculosis (TB), a disease endemic in Africa with a fatality of 1.5 million people per year , like COVID-19, is transmitted mainly by the respiratory route and affects the lungs[1,2]. In the literature, few studies have demonstrated the association and interactions between these two pathologies. However, the fragmented data reveal that tuberculosis with pulmonary localization must be considered as a potential risk factor for aggravation or complication of the disease. COVID-19, especially since the lung damage is significant, therefore In the fight against the COVID-19 pandemic, we must not forget to suspect and appropriately manage tuberculosis [2]. We report here the case of 3 patients who presented with COVID-19-Tuberculosis co-infection, treated at the level of the Epidemic Treatment Center (CTE) of the Thiès regional hospital in Senegal and whose evolution is favorable under early and adequate treatment.

Design of Streaming Data Transmission Using Rolling Shutter Camera-Based Optical Camera Communications

This paper addresses a method to transmit streaming data via rolling shutter camera-based optical camera communications (OCC). Since the amount of data that can be contained within one frame is limited, and the continuity of received data cannot be guaranteed due to OCC environmental variations, we introduce the concept of dividing the streaming data into several fragmented sets that are transmitted sequentially. We propose a superframe to contain sequential packets of fragmented data and corresponding indices, so that sequential packets for streaming data can be continuously collected. When redundant frame transmission is considered, any packet lost due to OCC environmental conditions can be recovered. Experimental results show that the proposed method can be successfully used to transmit streaming data, with the number of redundant frames required to acquire all data packets based on image resolution. In addition, we describe how to identify missing packets from a network point of view to reduce the number of redundant frames needed to acquire all the data. This paper presents baseline results of communication performance when sending streaming data via a rolling shutter-based OCC.

Short Bouts of Gait Data and Body-Worn Inertial Sensors Can Provide Reliable Measures of Spatiotemporal Gait Parameters from Bilateral Gait Data for Persons with Multiple Sclerosis

Wearable devices equipped with inertial sensors enable objective gait assessment for persons with multiple sclerosis (MS), with potential use in ambulatory care or home and community-based assessments. However, gait data collected in non-controlled settings are often fragmented and may not provide enough information for reliable measures. This paper evaluates a novel approach to (1) determine the effects of the length of the walking task on the reliability of calculated measures and (2) identify digital biomarkers for gait assessments from fragmented data. Thirty-seven participants (37) diagnosed with relapsing-remitting MS (EDSS range 0 to 4.5) executed two trials, walking 20 m each, with inertial sensors attached to their right and left shanks. Gait events were identified from the medio-lateral angular velocity, and short bouts of gait data were extracted from each trial, with lengths varying from 3 to 9 gait cycles. Intraclass correlation coefficients (ICCs) evaluate the degree of agreement between the two trials of each participant, according to the number of gait cycles included in the analysis. Results show that short bouts of gait data, including at least six gait cycles of bilateral data, can provide reliable gait measurements for persons with MS, opening new perspectives for gait assessment using fragmented data (e.g., wearable devices, community assessments). Stride time variability and asymmetry, as well as stride velocity variability and asymmetry, should be further explored as digital biomarkers to support the monitoring of symptoms of persons with neurological diseases.

Design of Streaming Data Transmission Using Rolling Shutter Camera-based Optical Camera Communications

This paper addresses a method to transmit streaming data via rolling shutter camera-based optical camera communications (OCC). Since the amount of data that can be contained within one frame is limited, and the continuity of received data cannot be guaranteed due to OCC environmental variations, we introduce the concept of dividing the streaming data into several fragmented sets that are transmitted sequentially. We propose a superframe to contain sequential packets of fragmented data and corresponding indexes, so that sequential packets for streaming data can be continuously collected. When redundant frame transmission is considered, any packet lost due to OCC environmental conditions can be recovered. Experimental results show that the proposed method can be successfully used to transmit streaming data, with the number of redundant frames required to acquire all data packets based on image resolution. In addition, we describe how to identify missing packets from a network point of view to reduce the number of redundant frames needed to acquire all the data. This paper presents baseline results of communication performance when sending streaming data via a rolling shutter-based OCC.